Iterator and Generator
Posted
tags:
篇首语:本文由小常识网(cha138.com)小编为大家整理,主要介绍了Iterator and Generator相关的知识,希望对你有一定的参考价值。
# Iterator 一个对象,代表了遗传数据流,使用__next__()方法或内置函数next()
# 返回连续的对象,没有数据返回时,抛出StopIteration异常
# iterable 一个对象,能每次返回数据组中的一个成员 for 循环中每次返回一个值 或
# 内置函数iter()传入参数返回iterator对象
# generator 使用了yield或者生成器表达式,申城iterator对象 用一种方便的
# 方法实现了iterator,在for循环取数据或使用next()取数据
# Iterator和Generator的关系
# 针对函数的列表进行优化
# 针对读取大文件进行优化
def gen_num():
yield 8
yield 99
yield 999
g = gen_num()
g
<generator object gen_num at 0x0000014F3F39EC50>
next(g) # 第一次运行
---------------------------------------------------------------------------
StopIteration Traceback (most recent call last)
<ipython-input-12-787e36cb69a2> in <module>()
----> 1 next(g) # 第一次运行
StopIteration:
def gen_num2():
for i in range(8):
yield i # yield有类似返回值return的效果
for g in gen_num2():
print(g) # 每次取一个值的时候,才生成这个值,节省内存
0
1
2
3
4
5
6
7
my_list = [1,2,3]
next(my_list) # 用 next方法验证是否为迭代器
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-17-4a97765cd86f> in <module>()
----> 1 next(my_list)
TypeError: ‘list‘ object is not an iterator
next(iter(my_list))
1
next(iter(my_list))
1
it = iter(my_list)
next(it)
1
next(it)
2
from collections import Iterator, Iterable
isinstance(my_list, Iterator)
False
isinstance(iter(my_list), Iterator)
True
isinstance((), Iterator)
False
isinstance((), Iterable) # 元组不是迭代器,但是可迭代
True
isinstance(range(8), Iterable)
True
isinstance(range(8), Iterator)
False
针对函数的列表进行优化
# Python 3:Fibonacci series up to n
def fib(n):
a, b = 0, 1
while a < n:
print(a, end=‘‘)
a, b = b, a+b
print()
fib(9)
0
1
1
2
3
5
8
def fil_list(n):
a, b = 0, 1
result = []
while a < n:
result.append(a)
a, b = b, a+b
return result
fil_list(55)
[0, 1, 1, 2, 3, 5, 8, 13, 21, 34]
fil_list(1000)
[0, 1, 1, 2, 3, 5, 8, 13, 21, 34, 55, 89, 144, 233, 377, 610, 987]
def fib_gen(n):
a, b = 0, 1
while a< n:
yield a
a, b = b, a+b
fib_gen(80)
<generator object fib_gen at 0x0000014F3EA593B8>
for i in fib_gen(80):
print(i)
0
1
1
2
3
5
8
13
21
34
55
[i for i in fib_gen(66)] # 列表推导式
[0, 1, 1, 2, 3, 5, 8, 13, 21, 34, 55]
针对读取大文件进行优化
import os
base_dir = r‘D:全栈全栈资料第三阶段 python进阶文件与日志-演示代码 2-autodata‘
log_path = os.path.join(base_dir, ‘access.log‘)
log_file = open(log_path)
log_data = log_file.readlines()
log_file.close()
len(log_data)
864
def read_log(log_path):
with open(log_path) as f:
print(‘Iterator:‘, isinstance(f, Iterator)) # open方法已经为我们生成一个迭代器
for line in f:
print(line)
break
read_log(log_path)
Iterator: True
220.181.7.76 - - [20/May/2010:07:26:23 +0100] "GET / HTTP/1.1" 200 29460 "-" "Baiduspider+(+http://www.baidu.com/search/spider.htm)"
列表推导式
[i for i in fib_gen(6)]
[0, 1, 1, 2, 3, 5]
m = [i for i in fib_gen(6)]
for i in m:
print(i)
0
1
1
2
3
5
生成器表达式
(i for i in fib_gen(5))
<generator object <genexpr> at 0x0000014F3EAC9C50>
n = (i for i in fib_gen(9))
for i in n:
print(i)
0
1
1
2
3
5
8
以上是关于Iterator and Generator的主要内容,如果未能解决你的问题,请参考以下文章
python generator iterator和iterable object